Competitive Constraints Research Articles

Mean Cold Pool Size of Quasi-Equilibrium Convection. Part II: The Survival Competition Hypothesis

Abstract The cold pool is a crucial component of tropical convection. However, what controls the mean cold pool size remains unclear. This two-paper series presents a theory of the mean cold pool radius in idealized quasi-equilibrium convection (Req). Part I derives an energy balance constraint between Req and the maximum potential radius of a cold pool (Rmax), showing that Req cannot reach Rmax. Cold pools must be densely packed and collide frequently. This Part II derives another constraint between Req and Rmax based on a cold pool survival competition hypothesis. A convective life cycle model with various candidate cold pool sizes is built. The type of cold pool producing the most intense next-generation cold pool is hypothesized to survive and set the spacing between convective towers. The size of the dominant cold pool type is determined by the trade-off between the mechanical lifting effect that favors a smaller cold pool, the thermodynamic forcing effect that favors a bigger cold pool, and the cloud radius feedback that also favors a bigger cold pool. Combining the energy balance and survival competition constraints, we obtain a solution for Req, which has an analytically tractable upper bound. The upper bound is set by the cold pool’s fractional entrainment rate and the free-tropospheric relative humidity: a lower fractional entrainment rate or a drier free troposphere raises the upper bound of Req. The Req predicted by the theory agrees with a set of large-eddy simulations with different rainwater evaporation rates.

Reinforced Collaborative-Competitive Representation for Biomedical Image Recognition.

Artificial intelligence technology has demonstrated remarkable diagnostic efficacy in modern biomedical image analysis. However, the practical application of artificial intelligence is significantly limited by the presence of similar pathologies among different diseases and the diversity of pathologies within the same disease. To address this issue, this paper proposes a reinforced collaborative-competitive representation classification (RCCRC) method. RCCRC enhances the contribution of different classes by introducing dual competitive constraints into the objective function. The first constraint integrates the collaborative space representation akin to holistic data, promoting the representation contribution of similar classes. The second constraint introduces specific class subspace representations to encourage competition among all classes, enhancing the discriminative nature of representation vectors. By unifying these two constraints, RCCRC effectively explores both global and specific data features in the reconstruction space. Extensive experiments on various biomedical image databases are conducted to exhibit the advantage of the proposed method in comparison with several state-of-the-art classification algorithms.

Product Market Competition and Financial Constraints: Evidence From Higher Education

Product Market Competition and Financial Constraints: Evidence From Higher Education

Information Technology Management System of Sharing Knowledge Between Universities Using Systematic Literature Review

Knowledge is a vital resource for academic institutions, driving innovation dan development. However, universities face challenges in effective knowledge sharing due to cultural barriers, lack of trust, and technological constraints. This research, conducted using a Systematic Literature Review (SLR), identifies key variables influencing knowledge sharing, highlights challenges, and proposes solutions to foster collaboration. The findings reveal that cultural barriers, such as competitive organizational environments and technological constraints, including high costs and user-friendly systems, significantly hinder knowledge sharing. To address these issues, the study recommends implementing user-friendly technologies, promoting collaboration through seminars and workshops, and encouraging cross-departmental projects. These solutions provide actionable insights to enhance knowledge sharing frameworks and support innovation across academic institutions

The effects of technology investment on financial stability: Evidence from commercial banks in Vietnam

This study examines the effects of technology investments on financial stability at commercial banks in Vietnam. Financial services provided by banks are vital to the growth and development of the Vietnamese economy. Due to competitive constraints and the need to keep up with fast-moving FinTech startups, Vietnamese banks have made digital transformation a top strategic goal. Therefore, the study aims to investigate the impact of technology investment on the financial stability of commercial banks in Vietnam from 2012 to 2023. The research used financial data from 26 joint-stock commercial banks and panel data analysis with the ordinary least squares (OLS), fixed effect model (FEM), random effects model (REM), and generalized method of moments (GMM) to look into the link between bank stability and technology spending. The findings reveal that while technology investment significantly enhances operational efficiency and market competitiveness, it poses risks, particularly during the initial stages of digital transformation. The results show a significant negative effect of technology investment on financial stability, highlighting the need for strategic planning and robust regulatory frameworks. These insights provide valuable recommendations for bank management and policymakers to balance technological advancements with financial stability, especially in economic disruptions like the COVID-19 pandemic. Finally, the practical implications help commercial banks strive to increase asset size and expand operations to strengthen financial capacity, increase brand recognition, create solid customer trust, improve competitiveness, and bring high profits.

Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups.

Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group-level processes such as subgroup formation and fission-fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals. We tracked 574 individuals from six species within the genus Canis in 15 countries on four continents with GPS telemetry to estimate the time that pairs of individuals within social groups spent in close proximity and test hypotheses regarding drivers of cohesion. Pairs of social canids (Canis spp.) varied widely in the proportion of time they spent together (5%-100%) during seasonal monitoring periods relative to both intrinsic characteristics and environmental conditions. The majority of our data came from three species of wolves (gray wolves, eastern wolves, and red wolves) and coyotes. For these species, cohesion within social groups was greatest between breeding pairs and varied seasonally as the nature of cooperative activities changed relative to annual life history patterns. Across species, wolves were more cohesive than coyotes. For wolves, pairs were less cohesive in larger groups, and when suitable, small prey was present reflecting the constraints of food resources and intragroup competition on social associations. Pair cohesion in wolves declined with increased anthropogenic modification of the landscape and greater climatic variability, underscoring challenges for conserving social top predators in a changing world. We show that pairwise cohesion in social groups varies strongly both within and across Canis species, as individuals respond to changing ecological context defined by resources, competition, and anthropogenic disturbance. Our work highlights that cohesion is a highly plastic component of animal sociality that holds significant promise for elucidating ecological and evolutionary mechanisms underlying cooperative behavior.

Ecosystem theories of harm in EU merger control: analysing competitive constraints and entrenchment

Ecosystem theories of harm in EU merger control: analysing competitive constraints and entrenchment

Impact of Government Subsidies on Green Innovation in Polluting Enterprises: A Review

To address the increasingly severe environmental challenges and achieve the "dual carbon" goals, the Chinese government has implemented a series of subsidy policies to promote green innovation and transformation of heavily polluting enterprises. However, against the backdrop of fierce market competition and tightening resource constraints, many companies still lack sufficient inherent motivation for green innovation. This study employs a systematic literature review method, analyzing relevant research from databases such as Web of Science, Scopus, and CNKI, aiming to systematically elucidate the research trajectory of government subsidies' impact on the green innovation performance of heavily polluting enterprises, thereby providing a theoretical perspective for improving relevant policy designs. The paper first posits that the logical starting point for government subsidies in green innovation lies in correcting environmental externalities, laying the foundation for subsequent discussions. It then examines the "incentive effect" and "crowding-out effect" of government subsidies on enterprises' green innovation performance, analyzes the non-linear relationship between government subsidies and corporate green innovation performance, and discusses the limitations of existing research from three aspects: relationship complexity, classification mechanisms, and influencing factors. Building on this, the paper integrates institutional theory with principal-agent theory to construct a multi-level analytical framework. This framework emphasizes the regulatory role of external institutional pressures, such as environmental regulations, on the effectiveness of subsidy implementation, while also focusing on how internal agency problems within enterprises may lead to inefficient utilization of subsidies, and how environmental information disclosure can help mitigate this issue. The study finds that there exists a non-linear relationship between subsidy intensity and green innovation performance, exhibiting "incentive effects" and "crowding-out effects" at different subsidy levels. Concurrently, factors such as environmental regulations, enterprise characteristics, and information disclosure practices play a moderating role in the effectiveness of subsidies. These findings have significant implications for policy-making, including designing subsidy schemes that avoid potential crowding-out effects at high subsidy levels, strengthening environmental regulations to enhance the effectiveness of R&D subsidies, implementing robust environmental information disclosure mechanisms, and formulating differentiated subsidy policies based on enterprise characteristics.

Influence of Adopting Electronic Procurement Practices on Performance of Supply Chain Management for Hospitals in Kenya

Technology has become an integral part of modern business, facilitating transactions and operations in many areas, including procurement. Businesses, clinics, and hospitals in Kenya have been quick to embrace E-Procurement strategies. In Kenyan hospitals, where e-procurement accounts for as much as 30% of operational expenses, this study seeks to evaluate the effect of this trend on supply chain management success. Companies that want to survive in today's cutthroat healthcare market must embrace e-procurement strategies if they want to keep up with the ever-changing industry. By facilitating more efficient inventory management, faster purchasing cycles, increased transparency, and higher quality services, e-procurement practices are essential for improving performance and competitiveness in the market. The health industry is facing severe competition and financing constraints, making it imperative that it reorganizes its service delivery system to adapt to the complicated business climate. The purpose of this empirical study is to investigate how hospitals in Kenya are using electronic tendering and electronic invoicing to improve their supply chain management. The study found that Kenyan hospital administrators have a highly positive perception of electronic procurement practices, with e-tendering scoring an average mean of 4.75, significantly enhancing SCM performance through efficiency and cost savings. The findings concluded that e-invoicing also positively impacts procurement processes, promoting transparency and operational effectiveness. The study further recommended that legislators integrate these electronic procurement practices into healthcare policies, provide financial assistance and training, and encourage hospitals to invest in robust systems and strategic partnerships to improve patient care and system efficiency.

Output feedback distributed economic model predictive control for parallel system in process networks

Abstract This paper proposes a distributed economic model predictive control algorithm for parallel systems which uses only output feedback. Such parallel systems are a fundamental system architecture frequently encountered in process networks where, in many cases, the state of the plant is not measurable. Economic performance is a key consideration in the operation of such industrial plants and it is of interest to develop theoretically rigorous approaches to tackle what is a practically very relevant scenario. The competitive couplings and competitive constraints inherent in parallel systems are explicitly addressed in the proposed controller design framework. Three measures are considered for optimization of such parallel systems including an economic stage cost function, energy efficiency and tracking accuracy. An economic cost function is optimized by the resulting distributed controller which can realize global control performance while also reducing the computational time for large-scale parallel systems. Stability of the system is formally proved using the principles of dissipativity. Finally, the effectiveness of the proposed theoretical approach is verified by both numerical simulation and experimentation to demonstrate practical relevance.

A warm dark matter cosmogony may yield more low-mass galaxy detections in 21-cm surveys than a cold dark matter one

ABSTRACT The 21-cm spectral line widths, $w_{50}$, of galaxies are an approximate tracer of their dynamical masses, such that the dark matter halo mass function is imprinted in the number density of galaxies as a function of $w_{50}$. Correcting observed number counts for survey incompleteness at the level of accuracy needed to place competitive constraints on warm dark matter (WDM) cosmological models is very challenging, but forward-modelling the results of cosmological hydrodynamical galaxy formation simulations into observational data space is more straightforward. We take this approach to make predictions for an ALFALFA-like survey from simulations using the EAGLE galaxy formation model in both cold (CDM) and WDM cosmogonies. We find that for WDM cosmogonies more galaxies are detected at the low-$w_{50}$ end of the 21-cm velocity width function than in the CDM cosmogony, contrary to what might naïvely be expected from the suppression of power on small scales in such models. This is because low-mass galaxies form later and retain more gas in WDM cosmogonies (with EAGLE). While some shortcomings in the treatment of cold gas in the EAGLE model preclude placing definitive constraints on WDM scenarios, our analysis illustrates that near-future simulations with more accurate modelling of cold gas will likely make strong constraints possible, especially in conjunction with new 21-cm surveys such as WALLABY.

How do financial constraints and market competition affect innovations: Evidence from Vietnam

This study delves into the effects of market competition and financial constraints on innovation within a transitional market. We implemented the Two Stage Least Squares regression to analyze a sample comprising 492 listed firms in Vietnam from 2008 to 2020. Our findings unveil an inverse U-shaped relationship between market competition and R&D intensity. Secondly, our study highlights the significant negative impact of financial constraints on R&D intensity. Thirdly, our research demonstrates the robustness of the nonlinearity of competition within small and medium-sized enterprises (SMEs). Our findings are consistent with agency theory, real options theory, and existing literature. Finally, our study offers practical implications for managers and policymakers aiming to foster innovation in developing countries, particularly amidst the digital transformation era.

Dynamic Bayesian game optimization method for multi-energy hub systems with incomplete load information

The interconnection of Energy Hub can enhance the energy efficiency and reliability associated with the independent operation of energy systems. However, the traditional optimal scheduling methods are hard to tackle the situation with the incomplete load information and competitive constraints of a multi-Energy Hub. This paper proposes a dynamic Bayesian game optimization scheduling strategy considering incomplete information on users’ load-side demand. First, a load forecast error coefficient is introduced to handle the conditional probability problem caused by incomplete information through the Bayesian rule. The constraint relationship among multi-Energy Hub under the dynamic price mechanism is analyzed to meet the economic and environmental coordination goals under load uncertainty. Second, extending from Nash equilibrium to Bayes Nash equilibrium proves the existence and uniqueness of Nash equilibrium solutions in Bayesian game models. The decision game algorithm is used to optimize the scheduling of the multi-Energy Hub and subsequently ensure the autonomous scheduling of the system and solve the information barriers. Finally, an Integrated Energy System composed of three Energy Hubs was used to validate the effectiveness and superiority of the proposed optimization method. Results show that under the Bayesian game decision, the multi-Energy Hub game model has reduced the total cost of the Integrated Energy System by 0.78 %, which can improve the economic benefit and address the environmental pollution problem.

Direct detections of the axionlike particle revisited

Axionlike particles (ALPs) are promising dark matter candidates. Their signals in direct detection experiments arise from the well-known inverse Primakoff effect or the inverse Compton scattering of ALPs with the electron. In this paper, we revisit the direct detection of ALP by carefully considering the interference between the inverse Primakoff amplitude and the inverse Compton amplitude in the scattering process a+e→e+γ for the first time. It shows that the contribution of the interference term turns to be dominated in the scattering for a large ALP energy. Given the new analytical formula, signals or constraints of ALP couplings in various projected experiments are investigated. Our results show that these experiments may put strong constraints on ALP couplings for relatively heavy ALP. We further study projected constraints on ALP from the JUNO experiment, which shows competitive constraints on ALP couplings using a ten-year exposure. Published by the American Physical Society 2024

Competition, Survival Issue, and Performance Constraints of Banks: Evidence from Ethiopian Private Commercial Banks

Banks are financial institutions that are crucial to the accomplishment of development objectives because they transfer money from surplus to deficit parties. This study examines the competition, survival, and performance constraints of commercial banks in Ethiopia using the DEA and CAMEL frameworks from 2015 to 2020. The nonparametric (DEA) approach was applied to approximate the overall technical efficiency score of the banks under consideration. The empirical study used twelve private commercial banks operating in Ethiopia, excluding four banks because of a lack of appropriate and audited financial data and no risk assessment between the study periods. The result of the study reveals that under CRS, except for Abyssinia, Anbesa, and Nib International Banks, the remaining banks are more efficient. Under VRS, while Abyssinia Bank was less efficient, other banks were found to be more efficient. Under scale efficiency, Abyssinia, Anbesa, and Nib International Banks were found to be less efficient, while the remaining banks were more efficient. The composite ranking of the CAMEL framework portrays that Awash International Bank, Zemen, and Wegagen Banks were found in the top three ranks, while Cooperative Bank of Oromia, Dashen, and Abyssinia Banks were found in the bottom position. The regression result demonstrates that the ratios of total capital to total assets, loans to assets, total loans to total deposits, and CAR have a positive effect on bank profitability, whereas the ratio of total loans to the number of branches has a statistically negative and significant influence on the return on assets.

Fiscal Policy for Inclusive Growth. A Case Study of Myanmar

Following decades of isolation under military rule, Myanmar initiated historic political reforms since 2011, but faces challenges translating liberalization into broad-based advancement. A dynamic stochastic general equilibrium modelling approach estimated on Myanmar data is used, with simulations quantifying potential growth and distributional impacts of strategic government expenditure reallocations towards infrastructure upgrading, agricultural investments, expanded social transfers and progressive tax reforms. Results indicate sustained infrastructure and rural productivity spending have high output multipliers while well-targeted transfers reduce income inequality. However, institutional absorptive capacities condition realization of social returns. Complementary governance enhancements like project oversight and competitiveness in public investment allocation prove vital. Regional peer benchmarking provides comparative lessons. Altogether, evidence-based fiscal reorientation towards addressing pressing human capital, rural-urban and firm competitiveness constraints can accelerate inclusive growth in Myanmar if pursued prudently. Sustainable expansion requires strengthening public financial management (PFM) systems and results monitoring.

Astrometric Microlensing by Primordial Black Holes with the Roman Space Telescope

Primordial black holes (PBHs) could explain some fraction of dark matter and shed light on many areas of early-Universe physics. Despite over half a century of research interest, a PBH population has so far eluded detection. The most competitive constraints on the fraction of dark matter comprised of PBHs (f DM) in the (10−9–10)M ⊙ mass ranges come from photometric microlensing and bound f DM ≲ 10−2–10−1. With the advent of the Roman Space Telescope with its submilliarcsecond astrometric capabilities and its planned Galactic Bulge Time Domain Survey (GBTDS), detecting astrometric microlensing signatures will become routine. Compared with photometric microlensing, astrometric microlensing signals are sensitive to different lens masses–distance configurations and contain different information, making it a complimentary lensing probe. At submilliarcsecond astrometric precision, astrometric microlensing signals are typically detectable at larger lens–source separations than photometric signals, suggesting a microlensing detection channel of pure astrometric events. We use a Galactic simulation to predict the number of detectable microlensing events during the GBTDS via this pure astrometric microlensing channel. Assuming an absolute astrometric precision floor for bright stars of 0.1 mas for the GBTDS, we find that the number of detectable events peaks at ≈103 f DM for a population of 1M ⊙ PBHs and tapers to ≈10f DM and ≈100f DM at 10−4 M ⊙ and 103 M ⊙, respectively. Accounting for the distinguishability of PBHs from stellar lenses, we conclude the GBTDS will be sensitive to a PBH population at f DM down to ≈10−1–10−3 for (10−1–102)M ⊙ likely yielding novel PBH constraints.

On the Galactic radio signal from stimulated decay of axion dark matter

We study the full-sky distribution of the radio emission from the stimulated decay of axions which are assumed to compose the dark matter in the Galaxy. Besides the constant extragalactic and CMB components, the decays are stimulated by a Galactic radio emission with a spatial distribution that we empirically determine from observations. We compare the diffuse emission to the counterimages of the brightest supernovæ remnants, and take into account the effects of free-free absorption. We show that, if the dark matter halo is described by a cuspy NFW profile, the expected signal from the Galactic center is the strongest. Interestingly, the emission from the Galactic anti-center provides competitive constraints that do not depend on assumptions on the uncertain dark matter density in the inner region. Furthermore, the anti-center of the Galaxy is the brightest spot if the Galactic dark matter density follows a cored profile. The expected signal from stimulated decays of axions of mass ma ∼ 10-6 eV is within reach of the Square Kilometer Array for an axion-photon coupling gaγ ≳ (2-3) × 10-11 GeV-1.

Green supply chain finance strategies with market competition and financial constraints

In the context of sustainable development, market competition is intensifying, and financial constraints have emerged as a significant hindrance to green project investment. Green Supply Chain Finance (GSCF), characterized by long-term collaboration, has emerged as a crucial financial approach to mitigate corporate financial limitations and channel capital flows into environmentally friendly industries. We propose a two-echelon supply chain with one supplier and two competing retailers over a single period and investigate ordering, sales, and financing decisions simultaneously under competition. Retailers constrained by financial considerations may secure GSCF or traditional bank financing (BF) loans. This study investigates the influence of competition on pricing and sales strategies during the selling season. The results demonstrate that retailers select between clearance and responsive selling strategies based on the level of market competition. During the ordering season, retailers share the product market equally when interest rates are uniform, and the supplier formulates a supply chain contract while considering the financing interest rate. In the presence of differential interest rates, retailers may not always opt for the GSCF, even when they offer an interest rate advantage, due to the comprehensive impacts of operational and financial strategies. Remarkably, competitive retailers do not choose the GSCF when their initial green investment capital surpasses a certain threshold.

Increased density of conspecifics caused niche contraction in a multispecific passerine assemblage.

Competition is a prominent mechanism driving population dynamics and structuring community assemblage, which can be investigated by linking shifts in species' ecological niche and the densities of sympatric species because the ecological release from competitive constraints is a density-dependent process. In this work we determine how a steppe passerine community segregates their ecological niches and evaluate the role of competition in inducing changes in the ecological niche of species. We built multidimensional ecological niches (with Gaussian kernel density estimators) using data on the habitat features used by 10 bird species collected from seven sites in the natural steppes of Central Spain over 2 consecutive years. We computed distance and niche similarity metrics to explore the ecological niche partitioning of the bird community. Next, we ran multivariate linear regression models to evaluate the effects of conspecific and heterospecific density (as proxies of intraspecific and interspecific competition, respectively) on niche breadth and/or position of the three most abundant species. We found low niche overlap in the community assemblage but varying levels of niche similarity among pairs of species, which could increase the likelihood of current competition operating in the community. However, we found no effect of heterospecific density on niche breadth or position, although conspecific density was negatively related to niche breadth. Contrary to predictions of competition theory, increased density of conspecifics caused niche contraction. Our results from a multispecies system contribute to advanced knowledge of the biotic mechanisms structuring wildlife communities within the framework of ecological niche theory.